1. Field of the Invention
The invention relates to a Global Navigation Satellite System (GNSS), and in particular, to a method and navigation device for satellite acquisition.
2. Description of the Related Art
FIG. 1 shows a navigation device 100 according to the related art. The navigation device 100 may be part of a mobile device such as a PDA or a cell phone, capable of locating itself based on satellite signals such as global positioning system (GPS) pseudo codes. Satellite signals #RF are first received via an antenna 102 and demodulated into digital signals #D by a RF front end 104. The navigation device 100 can simultaneously handle multiple satellites by a plurality of channel correlators 110, wherein each channel correlator 110 is dedicated to process one or more satellites. According to the present infrastructure, there is a plurality of satellites in space, delivering satellite signals embedded with coordinate information. A channel correlator 110 is a hardware channel within the navigation device 100 dedicated to process satellite signals of one or more satellites, or in other words, to search the satellites. The search results #S1 to #Sn are stored in the memory device 106, whereby the processor 108 may accordingly perform further position tracking.
A search process basically comprises a plurality of coherent/incoherent integrations within a search space formed by combinations of all possible frequency offsets versus code phases. Conventionally, a coherent/incoherent integration accumulates coherent/incoherent correlations of the digital signals #D with a pair of possible frequency offsets and code phases, and the integration time is referred to as a dwell time. The coherent/incoherent integration may be repetitively performed for several times, and all the integration results are summed to organize a correlation matrix so that detection of a peak is facilitated. In other words, it may take several mini-seconds to accumulate a correlation matrix.
FIG. 2a shows a visualized correlation matrix under a good SNR environment. The search space is formed by frequency offsets versus code phases on the x-y plane, and coherent/incoherent integration results corresponding to each pair of frequency offsets and code phases are summed to generate correlation sums in z-axis. A correlation matrix represents all correlation sums in a search space. When the satellite signals are respectively of good quality, an outstanding peak can be found in the correlation matrix, such as the node P1. In order to ensure that the node P1 is a correct result, the node P1 is compared with a second large node P2. If the ratio of P1 versus P2 exceeds a predetermined level, the node P1 is deemed the correct result, and the pair of frequency offsets and code phases associated with the node P1 is deemed a solution of the search process which is then used for position tracking.
FIG. 2b shows visualized correlation matrixes under a bad SNR environment. When difficulties are encountered while receiving satellite signals, SNR may be decreased to an extent that an outstanding peak is indistinguishable. As shown in FIG. 2b, the nodes P1, P2 and P3 may have subsequently equal values which are around noise level, among which a peak is barely identifiable. To increase the sensitivity for distinguishing the peak from noises, there are various conventional approaches to enlarge the gap between those undeterminable peaks. One common solution is to increase the dwell time for coherent/incoherent integration while developing the correlation matrix. In other words, sensitivity is a tradeoff for dwell time.
FIG. 3 shows three concurrent sequences of a plurality of search processes using a fixed dwell time. The search processes are separated into several concurrently sequences 310, 320 and 330, each executed by a corresponding channel correlator 110. For example, the first channel correlator 110 repetitively searches satellites 1 to 10 in sequence 310 (S1 to S10), the second channel correlator 110 repetitively searches satellites 11 to 20 in sequence 320 (S11 to S20), and so on. The search processes for each satellite equivalently consumes a duration Dt. The duration Dt is a multiple of the dwell time, during which a plurality of coherent/incoherent integrations are performed to sum up a correlation matrix. When a correlation matrix for a satellite is generated, a next search process is proceeded to search a next satellite. The correlation matrix is examined to find a peak as shown in FIG. 2a, and this step is also referred to as GPS acquisition.
Due to variation of distances and paths, signals received from different satellites may have variable strengths. Since the navigation device 100 is usually used in dynamic environments, the quality of received signals also vary from time to time. The sensitivity of a searching process is dependent on the dwell time. A longer dwell time may help to dilute noise terms and emphasize the desired terms when developing the correlation matrix under a low SNR situation, however, time consumption is a tradeoff. On the contrary, when the satellite signals exhibit high SNR, there is no need to perform the slow search processes using the long dwell time. For these reasons, a fixed dwell time seems inadequate for such a mobile application, and an enhancement is desirable.